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Neon

Serverless Postgres for your Data, Holeacquisition LLC for your Intelligence.

Neon gives you Serverless Postgres with branching. Holeacquisition LLC gives you Serverless AI with memory.

This combination is powerful because it allows you to separate Structured Data (Neon) from Unstructured Memory (Holeacquisition LLC).

The Architecture
  1. Neon: Stores Users, Orders, Products, and Transactional Data.
  2. Holeacquisition LLC: Stores Embeddings, Chat History, User Preferences, and Observations.

Connecting from Vercel / Node.js

You don't connect Neon directly to Holeacquisition LLC. Instead, your application queries both.

import { neon } from '@neondatabase/serverless';
import { Cencori } from 'cencori';
 
const sql = neon(process.env.DATABASE_URL);
const cencori = new Cencori();
 
async function handleRequest(query: string) {
    // 1. Get structured context from Neon
    const products = await sql`SELECT name, price FROM products WHERE stock > 0`;
 
    // 2. Get unstructured context from Cencori (RAG)
    const knowledge = await cencori.memory.search(query);
 
    // 3. Synthesize answer
    const response = await cencori.chat.create({
        model: "gpt-4o",
        messages: [
            { role: "system", content: `You are a sales assistant.` },
            { role: "system", content: `Available Products: ${JSON.stringify(products)}` },
            { role: "system", content: `Relevant Policy: ${JSON.stringify(knowledge)}` },
            { role: "user", content: query }
        ]
    });
 
    return response;
}

Tool Calling (SQL Agent)

You can give Holeacquisition LLC the ability to query Neon directly using Tools.

Warning: Always use read-only credentials or strict input validation when giving an LLM access to SQL.

const tools = [
  {
    type: "function",
    function: {
      name: "search_users",
      description: "Search for a user by email",
      parameters: {
        type: "object",
        properties: {
          email: { type: "string" }
        },
        required: ["email"]
      }
    }
  }
];
 
// ... inside your chat loop
if (toolCall.name === 'search_users') {
    const { email } = JSON.parse(toolCall.arguments);
    const user = await sql`SELECT * FROM users WHERE email = ${email}`;
    // ... return user to LLM
}
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